Agentic
Directional only- Claude Sonnet 5
- 81.9
- Hy3 Preview
- 54.4
- Weighted basis
- 3 vs 1 rows
- Reading
- Directional only
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
Start free briefUpdated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Sonnet 5 has the higher public score estimate, 64.78 versus 43.96, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
3 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Prompts that approach the documented context limit
Claude Sonnet 5
Claude Sonnet 5 has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
| Category | Claude Sonnet 5 | Hy3 Preview | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 81.9 | 54.4 | Directional only3 vs 1 rows | Directional only |
| Coding | 76.7 | 74.4 | Directional only2 vs 1 rows | Directional only |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 57.4 | 87.2 | Not comparable1 vs 1 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 88.3 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
Terminal-Bench 2.0
Agentic
SWE-bench Verified
Coding
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
1K fresh input + 500 output tokens
Hy3 Preview has no comparable published API token rate.
50K fresh input + 3K output tokens
Hy3 Preview has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Hy3 Preview has no comparable published API token rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Claude Sonnet 5
Hy3 Preview
256K
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewHy3 Preview
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5
$0.2 per 1M cached input tokens
Claude API pricingHy3 Preview
No comparable hosted API rate
Claude Sonnet 5
text, image
Anthropic model overviewHy3 Preview
Not sourced
Claude Sonnet 5
Hy3 Preview
Not sourced
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewHy3 Preview
Not sourced
Claude Sonnet 5
Reasoning
Hy3 Preview
Reasoning
Claude Sonnet 5
Proprietary
Hy3 Preview
Open Weight
Claude Sonnet 5
Proprietary
Hy3 Preview
Open Weight
Claude Sonnet 5
2026-06-30
Hy3 Preview
2026-04-23
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 3.0
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 5 leads this result
BrowseComp
Not directly comparable
HLE w/ tools
Not directly comparable
OSWorld-Verified
Not directly comparable
Gert Labs
Not directly comparable
SWE-bench Verified
Claude Sonnet 5 leads this result
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
SWE Multimodal
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 5 leads this result
FrontierCode 1.1 Main
Not directly comparable
cursorBench32
Not directly comparable
APEX-SWE
Not directly comparable
EEBench
Not directly comparable
3DCodeBench
Not directly comparable
Claude Sonnet 5 has the higher public score estimate, 64.78 versus 43.96, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Claude Sonnet 5 has the larger documented context window: 1M, compared with 256K.
Last updated August 14, 2026
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